tbuckley/cabot-search huggingface dataset:
Do bone scans over-stage disease compared to PSMA PET? An international multicenter retrospective study with blinded independent readers.
Authors: Wolfgang P. Fendler, Thomas A. Hope, Fei Jiang, Daniel Thompson, Francesco Barbato, Roxanna Juarez, Miguel Hernandez Pampaloni, Martin S. Auerbach, Pawan Gupta, Matthias R. Benz, Jeremie Calais
Journal: Journal of Clinical Oncology (2023)

5011 Background: PSMA positron emission tomography (PET) has a higher accuracy than computed tomography (CT) and bone scans to stage patients with prostate cancer. However, we do not understand how to apply clinical trial data based on conventional imaging to patients staged using PSMA PET. Therefore, we aim to evaluate the ability of bone scans to detect osseous metastases using PSMA PET as a reference standard. Methods: In this multicenter retrospective diagnostic study, 167 patients with prostate cancer, who were imaged with bone scan and PSMA PET performed within 100 days were included for analysis. Each study was interpreted by three blinded readers, and the results of the PSMA PET were used as the reference standard. Endpoints were positive predictive value (PPV), negative predictive value (NPV) and specificity for bone scans. Additionally, inter-reader reproducibility, positivity rate, uptake on PSMA PET, and number of lesions were evaluated. Results: 167 patients were included in the study, with 77 at initial staging, 60 in the BCR/CSPC setting and 30 in the CRPC setting. BS findings for metastatic disease validated by PSMA PET were tabulated. In all patients, the PPV, NPV and specificity for bone scans were 0.73 [0.61,0.82], 0.82 [0.74,0.88] and 0.82 [0.74,0.88]. In patients at initial staging, the PPV, NPV and specificity for bone scans were 0.43 [0.26,0.63], 0.94 [0.85,0.98], and 0.80 [0.68,0.88]. At initial staging 13/23 (57%) of positive bone scans were false positive. Inter-reader agreement for bone disease was moderate for bone scans (Fleiss k, 0.51) and substantial for the PSMA PET reference standard (Fleiss k, 0.80). Conclusions: In this multicenter retrospective study, the PPV of bone scans was low in patients at initial staging with majority of positive bone scans being false positives. This suggests that a large proportion of patients considered low volume metastatic by bone scan actually have localized disease. [Table: see text]
Efficacy and predictors of immune checkpoint inhibitors in patients with gallbladder cancer.
Authors: Zhuo Cheng, Cheng Yang, Qian Zhao, Jingjiao Zhong, Jin Zhang, Riming Jin, Yao Li, Na Ta, Dong Wu, Zhengang Yuan, Wen Sun, Ruoyu Wang
Journal: Journal of Clinical Oncology (2023)

e16124 Background: Immune checkpoint inhibitors (ICIs) targeting programmed cell death-1 (PD-1) or programmed cell death ligand-1 (PD-L1) has shown promising efficacy in multiple cancers including biliary tract cancers (BTCs). However, the data focusing on the efficacy of ICIs in patients with gallbladder cancer (GBC) is still limited. This study aims to assess the efficacy of ICIs in GBC and explore the clinicopathological and molecular markers of ICI benefit. Methods: This was a single center, retrospective study, including 80 GBC patients who had received ICI (anti-PD-1 monoclonal antibody) therapy at Eastern Hepatobiliary Surgery Hospital (Shanghai, China) between January 2016 and December 2020. Tumor samples from 31 of these patients who had previously underwent surgical resection before ICI therapy were obtained and conducted for whole exome sequencing and immunohistochemical analysis. The primary outcome was progression-free survival (PFS). The secondary outcomes were overall survival (OS), objective response rate (ORR) and disease control rate (DCR). The associations between efficacy with clinicopathological factors, genetic variations and PD-L1/CD8 expression were further explored. Results: Of 80 patients with GBC, 36 were male, the median age was 61 years (range, 30-79). The median PFS and OS was 4.5 months (95% CI, 2.99-5.95) and 8.7 months (95% CI, 7.07-10.26) respectively. Multivariate analysis indicated that alcohol intake history (HR, 2.66; 95% CI, 1.31-5.40; p=0.007), extrahepatic metastasis (HR, 2.03; 95% CI, 1.15-3.59; p=0.015), carcinoma embryonic antigen (CEA) level ≥100U/mL (HR, 3.58; 95% CI, 1.65-7.74; p=0.001) and immune-related adverse events (irAEs) (HR, 0.24; 95% CI, 0.10-0.57; p=0.001) were independent prognostic factors for PFS. Extrahepatic metastasis (HR, 2.42; 95% CI, 1.37-4.31; p=0.003), CEA level ≥100U/mL (HR, 2.82; 95% CI, 1.33-5.95; p=0.007) and irAEs (HR, 0.32; 95% CI, 0.14-0.72; p=0.006) were independent prognostic factors for OS. ORR and DCR were 13.75% and 37.5%, respectively. Patients with irAEs (85.7%, OR, 16.00; 95% CI, 3.26-78.61; p&lt;0.001), high CD8 + T-cells-infiltrated GBCs (87.5%, OR, 19.83; 95% CI, 2.00-196.38; p=0.011), immune inflamed phenotype (66.7%, OR, 5.60; 95% CI, 1.16-27.08; p=0.032) had higher DCR, while patients with high level of total bilirubin (TBIL&gt;34.2μmol/L) (8.3%, OR, 0.12; 95% CI, 0.01-0.97; p=0.048) had lower DCR. Patients with high CD8 + T-cells-infiltrated or immune inflamed GBCs also had a notably improved PFS and OS. Conclusions: ICIs were effective in patients with GBC. Alcohol intake history, extrahepatic metastasis, CEA level ≥100U/mL, irAEs, high positivity of CD8 + T-cells and immune inflamed phenotype may be useful for predicting the efficacy of ICIs in GBC.
Association of participation in Medicare’s Oncology Care Model with spending, utilization, and quality outcomes among commercially insured and Medicare Advantage members: A national difference-in-differences analysis.
Authors: Samyukta Mullangi, Benjamin Ukert, Gosia Sylwestrzak, Andrea DeVries, Stephanie Schauder, Elena Andreyeva, David Joseph Debono, Michael Jordan Fisch, Stephen Matthew Schleicher, Amol S. Navathe, Aaron L Schwartz, Justin E. Bekelman, Ravi Bharat Parikh
Journal: Journal of Clinical Oncology (2023)

1596 Background: Medicare’s Oncology Care Model (OCM) was a voluntary, episode-based model between 2016 and 2021 that provided participating practices with additional payments to fund care enhancements such as extended clinical hours and urgent care. While it resulted in net losses for traditional Medicare beneficiaries, the OCM may have had “spillover” improvements on spending, utilization, and quality for commercially insured (CM) and Medicare Advantage (MA) members who were not targeted by the program. Methods: This retrospective analysis used claims from Elevance Health, a large national payer, to identify commercially insured and Medicare Advantage members diagnosed with breast, colorectal, lung, prostate, and pancreatic cancer initiating systemic therapy between 2014 to 2021. We identified 85 OCM practices and 581 matched non-OCM practices based on episode, practice, demographic, and market factors. The exposure variable was participation in the OCM model. All outcomes were defined in 6-month episodes; the primary outcome was overall inflation-adjusted spending; secondary outcomes included hospitalization and emergency room visits, and end-of-life acute care utilization. We utilized adjusted difference-in-differences linear probability models, with state-level fixed effects to control for market price variability, to estimate the association between OCM participation and all outcomes. Results: We studied 45,296 episodes of care in OCM practices and 122,231 episodes in non-OCM practices among CM and MA members during the post-implementation period. OCM participation was associated with a $5,275 (SE $749.40) reduction in total allowed spending (p&lt;0.001), driven by reductions in outpatient and systemic therapy spending. OCM was associated with improvements in end-of-life utilization and ED visits but none in hospitalizations and timely chemotherapy initiation. Conclusions: Participation in the OCM was associated with modest spillover spending benefit onto CM and MA members, but minimal utilization and quality benefits. Resultant practice innovations may have benefited non-targeted patients. Evaluations limited to targeted patients may have underestimated the full impact of the OCM.[Table: see text]
Identification of prognostic tumor microenvironment in patients with advanced hepatocellular carcinoma treated with hepatic arterial infusion chemotherapy in combination with lenvatinib and PD-1 inhibitors.
Authors: Wenbo Guo, Song Chen, Lihua Zhao, Zhiqiang Wu, Hongjie Cai, Fan Wang, Lijia Wu
Journal: Journal of Clinical Oncology (2023)

e16141 Background: The triple combination therapy of hepatic arterial infusion chemotherapy (HAIC) combined with lenvatinib and programmed cell death protein-1 (PD-1) inhibitors has shown promising outcomes in patients with advanced hepatocellular carcinoma (HCC) as a first-line treatment. However, the tumor microenvironment (TME) characteristics of the beneficiary population are still unclear. This study aimed to generally explore the TME characteristics of patients receiving the triple combination therapy by baseline tumor tissues. Methods: A total of 44 patients were prospectively enrolled in this single-center study. Ultimately, 38 biopsy-proven patients were treated with HAIC with oxaliplatin, leucovorin, 5-fluorouracil (FOLFOX), lenvatinib, and PD-1 inhibitors. According to the tumor response elevated by the modified RECIST (mRECIST), the 38 patients were divided into the response group with complete response (CR) and partial response (PR) and the non-response group with stable disease (SD) and progression disease (PD). Overall survival (OS), progression-free survival (PFS), and adverse events (AEs) were evaluated. Meanwhile, the cancer gene-targeted next-generation sequencing (NGS) and RNA sequencing (RNA-seq) were performed to describe the differences between the two groups of biopsy samples to identify the prognostic TME characteristics. Results: Among the 38 patients, 22 patients were distributed to the response group, and the remaining 16 patients were included in the non-response group. The response group and the non-response group were significantly different in median OS (not-reached vs. 8.6 months; HR, 0.22, 95% CI 0.08-0.58; p&lt; 0.001) and median PFS (15.3 months vs. 2.0 months; HR, 0.31, 95% CI 0.13-0.75; p= 0.001). The most common AEs were AST elevation (84.2%), stomachache (76.3%), nausea (63.2%), and hypertension (52.6%). Grade 3/4 AEs occurred 14 times among 12 patients, and no treated-related deaths were observed. For the cancer gene-targeted NGS, no specific enrichment for gene mutations was identified to be related to prognosis. As for the TME analysis by RNA-seq, the response group was characterized by a more beneficial infiltration of immune cell subsets, and high tumor-infiltrating T lymphocytes were associated with a higher response rate, longer PFS and OS. Conclusions: In this study, HAIC plus lenvatinib and PD-1 inhibitor as first-line therapy displayed promising efficacy and manageable side effects in patients with advanced HCC. The differences in the initial TME of patients, especially in tumor-infiltrating T lymphocytes, may be potential biomarkers for predicting response and prognosis. This finding provides clues to search for biomarkers for the triple combination therapy of HAIC combined with lenvatinib and PD-1 inhibitors in advanced HCC.
Molecular and clinical characteristics of patients with KRAS mutated pancreatic ductal adenocarcinoma.
Authors: Alexander Hua Xiao, Aakash Desai, Thorvardur Ragnar Halfdanarson, Steven R Alberts, Robert R. McWilliams, Amit Mahipal, Tanios S. Bekaii-Saab, Qian Shi, Ryan Michael Carr, Wen Wee Ma
Journal: Journal of Clinical Oncology (2023)

e16259 Background: Patients with KRAS mutant (mt) pancreatic ductal adenocarcinoma (PADC) have worse survival outcomes compared to KRAS wild-type (wt) PDAC patients. However, the prognostic implication of the KRAS mutation subtype (e.g. G12D, G12R, G12V and Q61) remains unclear. Furthermore, the clinical and molecular characteristics associated with these mutation subtypes remain not well defined. Methods: A retrospective review was conducted on patients with KRAS PDAC who underwent Next Generation Sequencing at Mayo Clinic between December 1, 2018 and December 1, 2021. Their somatic mutations, RNA expression, demographics, disease characteristics, therapies offered, and clinical outcomes were collected via chart review. Results on KRAS wt were reported previously; KRAS mt are reported here. Results: A total of 158 KRAS mt patients (at diagnosis: average age 63.8 years, 57% male, 88 (56%) Stage IV) were included. 10% of patients had KRAS Q61 mutation, 14% G12R, 30% G12V and 46% G12D. G12R had a longer overall survival (OS) compared to the others (median 24.8 vs 17.5 months, unadjusted hazard ratio (HR) 0.68, p=0.05), particularly in patients with localized disease at diagnosis (median 35.4 vs 28.3 months, p=0.08). Among patients with metastatic disease at diagnosis, G12V had the lowest OS (median 9.8 vs 12.4 months, unadjusted HR 1.8, p=0.02). 137 (87%) patients had at least one pathogenic somatic variant, with statistically significant differences in SMAD4, TP53, MYC, RB1, KMT2D, RBM10, RNF43, KDM6A, KMT2C, RBM10, LRP1B, PIK3CA, and SMARC among the KRAS mt subtypes. 82 (52%) patients had at least one RNA expression variant, with statistically significant differences in CCND1, CCNE1, HRAS, MET, EGFR, and ERB3 among KRAS mt subtypes. Between these subtypes, there were no statistically significant differences in TMB value, location of PDAC or subsequent metastasis, lines of treatment (average 2.3), age at diagnosis, or gender. Conclusions: KRAS mt subtypes may confer different PDAC phenotypes. In our cohort, G12R is associated with improved OS while G12V correlates with worse prognosis in de novo metastatic disease. Additionally, there are differences in genomic variations and RNA expression between the KRAS mt subtypes. To further examine this, transcriptomic analysis is underway. [Table: see text]
Building liquid-liquid perfusion interface (LLPI) –based patient-derived tumoroids (PDTs) model system as clinical research tools for testing cancer therapeutics.
Authors: Pradeep Giri, Damieanus Ochola, Preethi Samuel, Jared Barrot, Bhuvanesh Dave
Journal: Journal of Clinical Oncology (2023)

e15192 Background: Current in vitro cancer model systems are inadequate in their representation and application of an actual tumor. Use of three-dimensional PDTs that consists of stroma and the microenvironment vastly addresses these shortcomings. However, a complete picture of the intratumoral interactions and functions requires optimal supply of oxygen to address problems associated with poor cellular oxygenation. Soft tissue sarcomas are malignant tumors that develop in the tissues that surround and support bones and organs. For non-resectable soft tissue sarcomas, model systems and treatment options are either limited or not available. We are establishing our Matrigel-based PDTs on a Liquid-Liquid Perfusion Interface (LLPI) using a synthetic hemoglobin as a blood substitute to build a comprehensive model system that is an amalgamation of an in vitro-in vivo system. Our objective is to replicate tumor complexity and use our model to serve as an effective and reliable platform to test and investigate therapeutic options. Methods: Soft tissue sarcoma PDT models with LLPI were built and used for testing under the following groups: Drug treatments with Doxorubicin (10nM), HSP90 inhibitor (1)10 nM, (2) 100 nM and (3) 1 mM) and combination (Doxorubicin + HSP90) for 10 days was compared on Sarcoma PDT models with and without oxygenation to test the impact of oxygen on tumor volume. Currently we are pursuing downstream analysis using apoptosis, proliferation and cytokine profiling and dynamic oxygen analysis of the TME. Results: We compared the effect of Doxorubicin with HSP90 inhibitor on a Sarcoma PDT model with and without oxygenation to observe the impact of oxygen on tumor growth. We observed similar rate of cell growth in the untreated samples in both model systems. In the non-oxygenated PDTs Doxorubicin-HSP90 combination was effective in reducing tumor volume. In the oxygenated PDTs the efficacy of the combination therapy (Doxorubicin+HSP90) was no longer observed. Conclusions: The oxygenation status impacts the effect of Doxorubicin, HSP90 combination, a critical influence that would not have been observable without the use of oxygenated PDT model system. The impact of intratumoral variations on oxygenation levels warrants testing other existing and novel therapeutics on oxygenated PDT model systems to investigate the extent of the influence of oxygenation on the tumor biology. [Table: see text]
Early death (ED) in elderly acute promyelocytic leukemia (APL) patients treated with lower induction doses of all-trans retinoic acid (ATRA).
Authors: Mark Dalgetty, Vamsi Kota, Anand P. Jillella, Locke Johnson Bryan, Anvay Shah, Sruthi Dontu, Priyanshu Nain, Isabela Pavkov
Journal: Journal of Clinical Oncology (2023)

e19012 Background: With the introduction of the differentiating agent ATRA, APL has progressed from being one of the most life-threatening diseases to becoming the most curable subtype of adult AML. However, despite this advancement, death within the first 30 days of treatment amongst elderly patients remains a critical issue with ED rates reportedly as high as 20-50%. There is limited data looking at the elderly population due to often being excluded from clinical trials given age associated with being prominent negative risk factor. Pharmacokinetic studies comparing 25 mg/m2/day and 45 mg/m2/day doses in adult patients have shown similar peak concentrations and mean area under the curve. Notably, low dose ATRA has been offered in pediatric patients in order to reduce incidence of differentiation syndrome. Differentiation syndrome is a key contributor to ED in elderly APL patients causing treatment failure. We propose that lower doses of ATRA in the elderly reduces the impact differentiation syndrome has on induction mortality amongst elderly APL patients and leads to a lower rate of ED. Methods: Fifteen APL patients &gt; 60 years of age were treated. Thirteen received low doses of ATRA (equal to or less than 25mg/m2/day) and two received standard doses of ATRA (45mg/m2/day). Arsenic trioxide was also used in addition to cytoreductive agents, such as cytarabine, hydroxyurea, and idarubicin as needed during induction. Dose reductions and regimens were based on age, comorbidities, and overall clinical judgement. During the course of treatment, further dose reductions and pauses in therapy were made based on clinical course. Results: A total of 15 elderly APL patients were treated between May 2017 and November 2020 at cancer centers within Georgia and South Carolina. The age range was 65-88 years old with a median age of 71 years old. 9/15 (60%) were female and 2/15 (13%) were classified as high risk. 13/15 were Caucasian and the remaining 2 were African American. Amongst the 13 APL patients who received lower doses of ATRA, one ED was noted. This occurred in 81-year-old Caucasian male with low risk APL who had multiple significant comorbidities and elected to halt treatment and pursue hospice. Amongst the 2 low risk APL patients who received standard doses of ATRA, one ED was noted due to differentiation syndrome. This patient also had many significant comorbidities. Conclusions: The ED rate in elderly APL patients treated with low doses of ATRA during induction was noted to be 1/13 (7.7%) which is significantly lower than what has been reported in literature. [Table: see text]
Using deep learning to recognize local advanced rectal cancer in CT images.
Authors: ChunYu Lin
Journal: Journal of Clinical Oncology (2023)

e15624 Background: Colorectal cancer was the most prevalent malignant disease in developed country and cause 45% mortality rate. Rectal cancer accounted 40% of this disease and is difficult to treat due to its anatomical position. Preoperative neoadjuvant radio-chemotherapy for local advanced rectal cancer can increase circumferential resection margin (CRM) which lead to lower local recurrence rate. MRI was suggested as staging methods for CRM status and nodal evaluation. However, MRI resources were much less than CT scans. CT scans was prevalent and can provide substantial agreement in CRM evaluation under experienced specialist. This study tries to use deep learning to detect local advanced rectal cancer in CT images at initiation of treatment as advisement for neoadjuvant chemoradiotherapy. Methods: From 2010.10.1~2021.12.31, rectal cancer patients with cT3-4 lesion was included. Collect high quality CT images with DICOM files in tumor segment. cT1-2, low rectal lesions, non-CRC cases were not included. Non-contrast and artificial defect images were also excluded. CT images were labeled as” diseased “ when CRM were threatened ( &lt; 2mm). All images were labeled according to judgment of 2 specialist. The data were separated into 2 parts. One for AI model training and testing, another for external validation. The training testing dataset was achieved by deep learning neuro network and evaluating model accuracy performance. Then the model was applied into external validation dataset for real-world testing, evaluating coherent rate between AI and the Dr. decision. Furthermore, to see the cancer survival outcomes according to AI model prediction results. Results: From 2010.10.1~2022.12.31, 1256 rectal cancer cases images were included. 706 cases (889 CT series, 5958 images) with cT3-4 lesions and high quality DICOM files were eligible. 620 cases (803 series, 5318 images) with cT3-4 lesions were classified in training validation set. 1907 (35.9%) images were diseased, 3411 (64.1%) images were normal. 86 clinical stage 2-3 cases (640 images) directly underwent resection during 2014.12.1-2017.5.31 were classified as external validation group. For recognizing CRM+ local advanced rectal cancer by EfficientNetB0, the algorithm achieved an area under the receiver operating characteristic curve (AUC): 0.91 (86.1% accuracy). For External validation set, the sensitivity for AI to detect CRM+ by Dr was 80%; 88% (by images; by cases), the specificity was 68%; 66% (by images; by cases). The survival curve (local recurrence rate, DFS, OS) was also superior in AI- group than AI+ group which was comparable with the results of Dr. Conclusions: Deep Learning can detect local advanced rectal cancer in CT images and prediction results also implicate poor disease outcome.